Bulletin of the American Physical Society
APS April Meeting 2022
Volume 67, Number 6
Saturday–Tuesday, April 9–12, 2022; New York
Session Y13: Analysis Techniques for Big DataRecordings Available
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Sponsoring Units: DAP GDS Chair: Bernard Kelly, University of Maryland, Baltimore County Room: Empire |
Tuesday, April 12, 2022 1:30PM - 1:42PM |
Y13.00001: Study of the Cosmic Ray Composition Sensitivity of AugerPrime Sonja Mayotte The AugerPrime upgrade of the Pierre Auger Observatory aims at enhancing the precision of primary particle composition measurements made by the Surface Detector. This is achieved by placing Surface-Scintilator-Detectors on top of the existing Water-Cherenkov-Detectors and comparing their differing responses to the electromagnetic and muonic components of extensive air showers as the ratio of these components is strongly related to the mass of the primary cosmic ray. While the deployment of the upgrade is ongoing, the composition sensitivity of AugerPrime can be probed using current machine learning techniques on simulations containing a mixed composition of protons, helium, oxygen, and iron. |
Tuesday, April 12, 2022 1:42PM - 1:54PM |
Y13.00002: Searching for Sub-threshold Gravitational Wave Candidates with RAVEN Brandon J Piotrzkowski RAVEN, the Rapid on-source VOEvent Coincidence Monitor, is a low-latency pipeline searching for coincidences between gravitational wave candidates and astrophysical alerts external to the LIGO-Virgo-KAGRA collaboration, including gamma-ray and neutrino bursts. RAVEN calculates a joint false alarm rate using timing and spatial information from coincident events with the goal of increasing the significance of sub-threshold binary neutron star, neutron star-black hole, and unmodelled gravitational wave candidates for public release. RAVEN will help in increasing the population of joint observations and improve the chances of subsequent EM observations, especially if joint EM-GW sky-maps are more constrained and more accurate. |
Tuesday, April 12, 2022 1:54PM - 2:06PM |
Y13.00003: A Systematic MillimeterTransient Seach Using ACT Data Emily Biermann, Yaqiong Li, Arthur Kosowsky Until now the millimeter transient sky has been largely unobserved. However, CMB surveys now have high enough resolution to study these events. The Atacama Cosmology Telescope (ACT) is a 6-meter telescope with arcminute-scale angular resolution that is primarily used to study the cosmic microwave background. The telescope covers roughly 40 percent of the sky with a weekly cadence and provides sufficient resolution to study millimeter waveband transient events. We conducted a systematic search of three years of ACT data using mean subtracted maps with CMB, asteroids, planets and bright sources removed. We begin searching for transients with a signal to noise cut of 5, taking the position to be the center of mass by flux. Next, we cut spurious sources close to the edges of the maps, clustered in large groupings, or along zero variance contours. Finally, we cross match each event across different frequencies and arrays. Any source which does not appear in at least two arrays is considered spurious. Once all the data cuts are complete we are left with 524 candidate events. There are 73 independent sources and the majority have several repeated events. We identify each candidate by cross matching with external catalogs and by studying their lightcurves. |
Tuesday, April 12, 2022 2:06PM - 2:18PM |
Y13.00004: EeV photons from the Pierre Auger Observatory: a Real-time probe for Multi-messenger analyses Pierpaolo Savina, Lu Lu The quest for the origin of cosmic rays intrinsically implies a multi-messenger approach. Due to magnetic fields that permeate the universe, cosmic rays, which are mostly charged ions, do not point back to the sources. Direct information about their acceleration sites can, however, be obtained by searching for the neutral particles, gamma-rays and neutrinos, that can be generated by the interactions of cosmic rays at the acceleration sites. In this work, the search for nearby ultra-high-energy transient sources is addressed by performing a search for photon candidates among the events collected by the Pierre Auger Observatory. The goal, in the future, is to perform a real-time coincidence search with neutrinos collected by the IceCube Observatory. |
Tuesday, April 12, 2022 2:18PM - 2:30PM |
Y13.00005: Vision Transformer for Gamma-Hadron Classification with the HAWC Observatory Baek Sun Cho, Ian J Watson, Myeonghun Choi The High Altitude Water Cherenkov (HAWC) gamma-ray observatory consists of 300 water Cherenkov detectors, each of which contains four photomultiplier tubes (PMTs). In the atmosphere, both cosmic rays and gamma rays produce air showers containing cascades of ionized particles and electromagnetic radiation. We train a neural network to distinguish gamma-ray events from cosmic ray events using a novel semi-supervised method, which uses real data to train the network. We show that the network trained using our method outperforms a network trained with simulated data. |
Tuesday, April 12, 2022 2:30PM - 2:42PM |
Y13.00006: Weakly-Supervised Anomaly Detection in the Milky Way Matthew R Buckley, Jack Collins, Benjamin Nachman, Mariel Pettee, David Shih, Sowmya Thanvantri Large-scale astrophysics datasets, such as the 1 billion Milky Way stars from the Gaia satellite, present an opportunity for novel machine learning techniques to identify regions of interest that might otherwise be overlooked by traditional techniques. We use a weakly-supervised anomaly detection technique, Classification Without Labels (CWoLa), to identify cold stellar streams within the Gaia dataset. CWoLa operates without the use of labeled anomalies or knowledge of astrophysical principles. Instead, we train a classifier to distinguish between mixed samples in which class proportions need not be known. This technique, originally designed for collider physics, has broad applicability within astrophysics as well as other domains interested in identifying anomalous localized features. |
Tuesday, April 12, 2022 2:42PM - 2:54PM |
Y13.00007: Using Evolutionary Algorithms to Design Antennas with Greater Sensitivity to Ultra-High Energy Neutrinos Ryan T Debolt Genetic Algorithms or GAs are useful tools for efficiently solving problems with high dimensional parameter spaces. GAs are modeled after the biological evolution of species and can be used in a multitude of applications, such as data classification, multivariate regression, and parameter optimization. The GENETIS collaboration uses these algorithms to optimize for a science outcome, specifically, antenna designs for the detection of UHE neutrino-induced radio pulses. We use two different approaches to accomplish this. First, we use the more traditional method of optimizing geometric designs. Using Remcom’s finite-difference time-domain modeling program, XFdtd, we simulate antenna response patterns that are then used in a neutrino in-ice detector simulation to assign a fitness score. Our second approach opts to design the response patterns directly to quantify the potential for improvement of our fitness scores. Here we will show that using these techniques, we were able to create a design with 22% greater sensitivity to in-ice UHE neutrino detection than the VPol antennas currently in use. |
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